Building intuition for p-values and statistical significance

Marton Trencseni - Sun 25 April 2021 • Tagged with ab-testing

This is the transcript of a talk I did on experimentation and A/B testing, to give the audience an intuitive understanding of p-values and statistical significance.

Coin flip

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Random numbers, the natural logarithm and higher dimensional simplexes

Marton Trencseni - Sat 17 April 2021 • Tagged with bayesian, ab-test

The base $e$ of the natural logarithm shows up in an unexpected place. Let's derive why!

Simplex

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Building a Pytorch Autoencoder for MNIST digits

Marton Trencseni - Thu 18 March 2021 • Tagged with pytorch, autoencoder, mnist

I build an Autoencoder network to categorize MNIST digits in Pytorch.

Conversion difference vs N

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Training a Pytorch Wasserstein MNIST GAN on Google Colab

Marton Trencseni - Wed 03 March 2021 • Tagged with ab-testing

I train a Pytorch Wasserstein MNIST GAN on Google Colab to beautiful MNIST digits.

Wasserstein GAN Generated MNIST digits

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Training a Pytorch Classic MNIST GAN on Google Colab

Marton Trencseni - Tue 02 March 2021 • Tagged with ab-testing

I train a Pytorch Classic MNIST GAN on Google Colab to generate MNIST digits.

Classic GAN Generated MNIST digits

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Training a Pytorch Lightning MNIST GAN on Google Colab

Marton Trencseni - Sat 20 February 2021 • Tagged with python, pytorch, gan, mnist, google-colab

I explore MNIST digits generated by a Generative Adversarial Network trained on Google Colab using Pytorch Lightning.

Softmax GAN after 5 epoch, 100 samples.

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Automatic MLFlow logging for Pytorch

Marton Trencseni - Sun 24 January 2021 • Tagged with mlflow, tracking

I explore the automatic logging capabilities of MLFlow for Pytorch.

MLFlow Pytorch loss example.

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Automatic MLFlow logging for Scikit Learn

Marton Trencseni - Fri 15 January 2021 • Tagged with mlflow, tracking

I explore the automatic logging capabilities of MLFlow for Scikit Learn. In the process I found a bug in MLFlow, reported it and wrote a pull request to fix it.

MLFlow scatter plot.

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Getting Started with MLFlow

Marton Trencseni - Sun 10 January 2021 • Tagged with mlflow, tracking

For the last few months I’ve been using MFlow in production, specifically its Tracking component. MLFlow is an open source project for lifecycle tracking and serving of ML models, coming out of Databricks. MLFlow is model agnostic, so you can use with SKLearn, XGBoost, Pytorch, Tensorflow, FBProphet, anything.

MLFlow overview

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Making statistics lie for the 2020 Presidential election

Marton Trencseni - Thu 17 December 2020 • Tagged with ab-testing

After the 2020 US presidential election, the Trump campaign filed over 50 lawsuits and attacked the integrity of the elections by claiming there was voter fraud. One of the last lawsuits was filed in the Supreme Court of the United States by the state of Texas. Here I look at the statistical claims made in this lawsuit that were supposed to show irregularities in the Georgia vote.

Trump vs Biden

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